Lessons on Ocean Governance through the Historic Management of Indigenous Coastal Territories: The Short Comings of Modern Maritime Legislation in the Search for an Equitable Ocean Future
Bibliographic record
Abstract
The oceans cover a 70% of our planet and play a key role in environmental, economic, and cultural activities \nfor communities around the world. However, access to ocean resources is not equitable. It is often small, \nminority communities that are excluded from the decision-making processes that impact them the most. \nAmong the most vulnerable stakeholders in the face of ocean change are coastal indigenous communities. \nGiven recent initiatives to promote global ocean equity, this study investigated the impacts of the United \nNations Convention on the Law of the Sea (UNCLOS) on narratives of maritime indigenous governance \naround the world. A comparative case-study analysis of indigenous legislation in international straits in \nAustralia and Canada aimed to determine whether future ocean equity initiatives should take a bottom-up \napproach to indigenous maritime rights or whether reformation of international legislation is necessary. \nStudy findings demonstrated that while Australian and Canadian approaches to indigenous governance \nvaried, UNCLOS uniformly hindered the ability of indigenous communities to take part in governance of \ncoastal space. With a state centric approach to ocean governance, UNCLOS consistently supported the \nomission of indigenous stakeholders from the decision-making process. As a result, this study recommends \nthe amendment of UNCLOS to recognize and empower indigenous peoples to take control of their \ntraditional lands. Additionally, this study encourages the reinforcement of regional governance \ninfrastructure in international straits to promote the implementation tailored management strategies for \nthese vulnerable coastal areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.047 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".